Flashcards in Hypothesis testing Deck (18)

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1

## What are parametric data?

### data that are normally distrubuted

2

## What are 3 types of hypotheses you can test?

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1. Single sample (comparing a sample to a known value e.g. average weight of woman in USA)

2. two independent samples (comparing two experimental conditions and different participants were assigned to each condition)

- two groups of subjects in two different conditions (experimental and control)

3. two dependent samples (two experimental conditions and the same participants took part in both conditions of the experiment)

- same group of subjects in the conditions

3

## What is the null hypothesis?

### he position that any difference is simply due to sampling error (chance variation)

4

## What is the alternate hypothesis?

### the position that any difference is not due to sampling error but rather due to the effect of the experimental manipulation

5

## What are the 8 steps of hypothesis testing?

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1. choose a hypothesis to test

2. choose an alternate hypothesis

3. choose a significance level

4. determine the distribution

5. determine the critical region

6. establish a rejection rule

7. calculate the statistic

8. draw the appropriate conclusion

6

## What is alpha

### he probability of making a Type I error

7

## what is beta

### the probability of making a Type II error

8

## what is power

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the probability of correctly rejecting the null hypothesis when the null hypothesis is false (i.e. the probability of NOT making a type 2 error)

Probability that a given test will find an effect assuming that one exists in the population

9

## what is a type 2 error

### Incorrectly failing to reject the null hypothesis when the null hypothesis is false

10

## what is a type 2 error

### Incorrectly failing to reject the null hypothesis when the null hypothesis is false

11

## What factors influence alpha?

### the researcher (based on the consequences of committing a type 1 error)

12

## What are the factors that affect beta? (6)

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1. alpha

2. the alternative hypothesis

3. the size of the samples (large sample = more power)

4. the real difference between the two means (the magnitude of the true difference i.e. effect size)

5. parametric vs non-parametric tests (parametric have more power)

6. independent- vs dependent-groups designs

13

## how do you calculate the probability of rejecting the null hypothesis? (power)

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Need to base this on comparing 2 distributions

- the distribution you would get if the null hypothesis was true vs if the null is false

14

## How does independent- vs dependent-groups designs impact power?

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By impacting amount of variability

-> dependent group designs have fewer sources of variability and therefor more power to detect a treatment effect

15

## What are the sources of variability in an dependent groups (within groups) t test?

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1. Experimental error

2. Treatment effect

16

## What are the sources of variability in an independent groups (between groups) t test?

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1. Experimental error

2. Individual differences

3. Treatment effect

17

## What is experimental error

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1. fluctuations in external conditions (e.g. room temperature, lighting)

2. temporary variations in the subjects themselves (e.g. distracted, tired)

18